This paper presents the orthogonal direction vanishing points detection algorithm for scene image. It use the Hough transform to detect straight lines in the image, then it based on RANSAC robust framework to calculate the initial value, the end use of Levenberg-Marquardt algorithm for nonlinear optimization iteration to strike the final vanishing point. The experiments result shows that the algorithm can not only quickly detect scene orthogonal direction vanishing points, but also high-precision and that respected this method suitable for use in a scene with large buildings or hyperopia scene.
This paper presents an operator that fitting the parameters of ellipses features, and improves the computational efficiency. Based on the dual conic model, this operator directly uses the raw gradient information in the neighborhood of an ellipse’s boundary, which use tangent lines and to apply the estimation in the dual space, so that avoiding the step of precisely extracting individual edge points. Moreover, under the dual representation, the dual conic can easily be constrained to a dual ellipse when minimizing the algebraic distance. The operator presents low sensitivity to noise and is compared to other estimation approaches, which shows good results, the accuracy of this operator is the highest, the time of this operator is moderate that compared with the other methods, and fall within acceptable levels, and in the case of noise or blur, the algorithm have shown very good robustness, in the practical environment can fit the parameters of the ellipse accurately.
SIFT is the most common algorithm for the image local feature points matching. The excellency of it is not only good spatial scale invariance, but also more accurate and faster than other algorithm. However, the SIFT feature points do not reflect the geometric features of objects, so, when dealing with the building images, these points are not available in most cases, and the extraction process is complicated. Therefore, this paper presents a new algorithm that combines the Harris corner detector and SIFT operator. This new algorithm not only can enhance the efficiency of image matching, and make accurate information on the building corner, but also provide good reference information for modeling. Experiments show that the extract feature points of this algorithm can be applied to the three-dimensional reconstruction of large buildings.
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